The present invention relates generally to gaming machines and, more particularly, to a self-learning gaming machine that adjusts a parameter of a game for future plays based on a player""s selection affecting an outcome of a current play.
Gaming machines, such as slot machines, video poker machines and the like, have been a cornerstone of the gaming industry for several years. Generally, the popularity of such machines with players is dependent on the likelihood (or perceived likelihood) of winning money at the machine and the intrinsic entertainment value of the machine relative to other available gaming options. Where the available gaming options include a number of competing machines and the expectation of winning each machine is roughly the same (or believed to be the same), players are most likely to be attracted to the most entertaining and exciting of the machines. Shrewd operators consequently strive to employ the most entertaining and exciting machines available because such machines attract frequent play and hence increase profitability to the operator. Accordingly, in the competitive gaming machine industry, there is a continuing need for gaming machine manufacturers to produce new types of games, or enhancements to existing games, which will attract frequent play by enhancing the entertainment value and excitement associated with the game.
A self-learning gaming machine comprises a game of chance executed by a processor in response to a wager. The game includes a plurality of symbol-bearing indicia and an adjustable parameter. The adjustable parameter is adjusted by the processor for future plays of the game based on a player""s selections affecting outcomes of at least one previous plays. During the previous play, the player""s selection is made after the plurality of symbol-bearing indicia are displayed.